Principal Component Analysis to analyze a breast tumor dataset

About

This is the codebase for the section VI of my paper, where principal component analysis (PCA) is applied to a breast tumor dataset. All graphics and results used can be generated using the pca.iypnb notebook.

For more information about PCA and its derivation and application, please refer to my paper (pca.pdf)

Setup using Poetry

For an easier setup, use poetry as the dependency management.

# clone this repo with 
git clone https://github.com/chrissiwaffler/pca-breast-tumor.git

# installing all python dependencies
poetry install

Afterwards, make sure to select the poetry virtual environment when starting the IPython kernel.

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All results and explanation of the approach are documented in the Jupyter notebook (pca.ipynb) file. Figures generated by the Notebook are saved in the figures/ directory.